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Contents lists available at ScienceDirect
Behaviour Research and Therapy
journal homepage: www.elsevier.com/locate/brat
Subtyping children and adolescents with loss of control eating by
negative affect and dietary restraint
Andrea B. Goldschmidt a, Marian Tanofsky-Kraff b,, Lien Goossens c, Kamryn T. Eddy d,e,1,
Rebecca Ringham f, Susan Z. Yanovski b,g, Caroline Braet c, Marsha D. Marcus f, Denise
E. Wilfley h, Jack A. Yanovski b
a
Department of Psychology, Washington University, 660 South Euclid Avenue, Campus Box 8134, St. Louis, MO 63110, USA
Unit on Growth and Obesity, PDEGEN, Eunice Kennedy Shriver, National Institute of Child Health and Human Development, National Institutes of Health,
Hatfield Clinical Research Center, Room 1-3330, MSC 1103, Bethesda, MD 20892, USA
c
Department of Developmental, Personality and Social Psychology, Ghent University, Henri Dunantlaan 2, 9000 Ghent, Belgium
d
Center for Anxiety and Related Disorders, 648 Beacon Street, 6th Floor, Boston, MA 02215, USA
e
Children’s Hospital Boston, 300 Longwood Avenue, Boston, MA 02115, USA
f
Western Psychiatric Institute and Clinic, University of Pittsburgh Medical Center, 3811 O’Hara Street, Pittsburgh, PA 15213, USA
g
National Institute of Diabetes and Digestive and Kidney Diseases, 6707 Democracy Boulevard, Room 675, Bethesda, MD 20892, USA
h
Department of Psychiatry, Washington University School of Medicine, 660 South Euclid Avenue, Campus Box 8134, St. Louis, MO 63110, USA
b
a r t i c l e in fo
abstract
Article history:
Received 17 November 2007
Received in revised form
8 February 2008
Accepted 11 March 2008
Objective: Research suggests that subtyping adults with binge eating disorders by dietary
restraint and negative affect predicts comorbid psychopathology, binge eating severity,
and treatment outcome. Little research has explored the validity and clinical utility of
subtyping youth along these dimensions.
Method: Children (aged 8–18 years) reporting loss of control eating (n ¼ 159) were
characterized based upon measures of dietary restraint and negative affect using cluster
analysis, and then compared regarding disordered eating attitudes and behaviors, and
parent-reported behavior problems.
Results: Robust subtypes characterized by dietary restraint (n ¼ 114; 71.7%) and dietary
restraint/high negative affect (n ¼ 45; 28.3%) emerged. Compared to the former group,
the dietary restraint/high negative affect subtype evidenced increased shape and weight
concerns, more frequent binge eating episodes, and higher rates of parent-reported
problems (all pso0.05).
Conclusion: Similar to findings from the adult literature, the presence of negative affect
may mark a more severe variant of loss of control eating in youth. Future research should
explore the impact of dietary restraint/negative affect subtypes on psychiatric functioning, body weight, and treatment outcome.
& 2008 Elsevier Ltd. All rights reserved.
Keywords:
Loss of control eating
Negative affect
Dietary restraint
Children
Adolescents
Corresponding author. Present address: Department of Medical and Clinical Psychology, Uniformed Services University of the Health Sciences, 4301
Jones Bridge Road, Bethesda, MD 20814, USA. Tel.: +1 301 295 1482; fax: +1 301 295 3034.
E-mail addresses: goldscha@psychiatry.wustl.edu (A.B. Goldschmidt), mtanofsky@usuhs.mil (M. Tanofsky-Kraff), lien.goossens@ugent.be (L.
Goossens), kamryn@gmail.com (K.T. Eddy), ringhamrm@upmc.edu (R. Ringham), yanovskis@extra.niddk.nih.gov (S.Z. Yanovski), caroline.braet@ugent.be
(C. Braet), marcusmd@upmc.edu (M.D. Marcus), wilfleyd@psychiatry.wustl.edu (D.E. Wilfley), yanovskj@mail.nih.gov (J.A. Yanovski).
1
Present Address: Massachusetts General Hospital/Harvard Medical School, 2 Longfellow Place, Suite 200, Boston, MA 02114, USA.
0005-7967/$ - see front matter & 2008 Elsevier Ltd. All rights reserved.
doi:10.1016/j.brat.2008.03.004
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Introduction
Research in adults with binge eating disorder (BED) and bulimia nervosa (BN) suggests the presence of two distinct
subtypes, one characterized by pure dietary restraint (i.e., cognitive and/or behavioral aspects of dieting, such as desire to
limit food intake in the absence of overt behavioral efforts to do so, and/or actual behavioral efforts to limit food intake,
respectively; Lowe & Timko, 2004), and the other by a mixed presentation combining dietary restraint and negative affect.
The latter subtype has been consistently found to co-occur with increased psychiatric symptoms in adults, including
greater shape and weight concerns, increased psychopathology and personality disturbances, poorer treatment response,
and, in some cases, greater severity and chronicity of binge eating (Grilo, Masheb, & Berman, 2001; Grilo, Masheb, &
Wilson, 2001; Loeb, Wilson, Gilbert, & Labouvie, 2000; Stice & Agras, 1999; Stice et al., 2001; Stice & Fairburn, 2003).
To date, however, no association has been found with regard to dietary restraint/negative affect subtypes and body mass
index (BMI; kg/m2) in adults (Grilo, Masheb, & Berman, 2001; Grilo, Masheb, & Wilson, 2001; Loeb et al., 2000; Stice &
Agras, 1999; Stice et al., 2001; Stice & Fairburn, 2003).
Loss of control eating (LOC; the feeling that one cannot control what or how much one is eating) and binge eating
(consumption of an unambiguously large amount of food accompanied by LOC; American Psychiatric Association, 1994)
behaviors are common in children and adolescents (Glasofer et al., 2007; Tanofsky-Kraff et al., 2004). LOC while eating in
childhood has been associated with overweight and excess body fat (Field et al., 2003; Stice, Presnell, Shaw, & Rohde, 2005;
Stice, Presnell, & Spangler, 2002; Tanofsky-Kraff et al., 2004, 2006), and with a higher degree of eating-related and general
psychopathology (Decaluwe & Braet, 2003; Goldschmidt et al., 2008; Goossens, Braet, & Decaluwe, 2007; Morgan et al.,
2002; Tanofsky-Kraff, Faden, Yanovski, Wilfley, & Yanovski, 2005). Similar to adults with binge eating (e.g., Chua, Touyz, &
Hill, 2004; Fairburn et al., 1998; Fairburn, Welch, Doll, Davies, & O’Connor, 1997; Telch & Agras, 1996), negative affect and
dietary restraint each has been implicated in the onset and maintenance of LOC and binge eating in youth. Children with
LOC eating problems are more likely to exhibit depressive symptoms than weight-matched peers (Decaluwe & Braet, 2003;
Eddy et al., 2007; Goossens et al., 2007; Isnard et al., 2003; Morgan et al., 2002; Tanofsky-Kraff et al., 2005), and prospective
data confirm that negative affect precedes and predicts binge eating in youth (Stice & Agras, 1998; Stice, Killen, Hayward, &
Taylor, 1998; Stice et al., 2002). According to several theories of affect regulation, binge eating may serve to modulate
negative affect. For example, binge eating may provide a distraction from external stressors (Heatherton & Baumeister,
1991) or enable a ‘‘trade-off,’’ whereby the aversive emotions preceding binge eating (e.g., anger) are replaced by less
aversive emotions subsequent to binge eating (e.g., guilt; Kenardy, Arnow, & Agras, 1996). Indeed, preliminary evidence
suggests that youth with LOC eating problems are more likely than those without eating problems to endorse emotional
eating in general (Goossens et al., 2007; Tanofsky-Kraff, Theim et al., 2007), and to report that LOC eating episodes occurred
in response to a negative emotion (Tanofsky-Kraff, Goossens et al., 2007).
The literature concerning the role of dietary restraint in the onset of LOC eating in children has been less consistent.
Restraint Theory, which posits that binge eating results from perceived lapses in strict dietary restraint (Polivy & Herman,
1985), has received some support in the empirical literature, with prospective evidence indicating that dietary restraint
predicts the onset of binge eating in youth (Stice et al., 1998, 2002). Whereas by adulthood, most individuals with BN and
BED report an extensive dieting history (e.g., de Zwaan et al., 1994; Kurth, Krahn, Nairn, & Drewnowski, 1995), some
(Decaluwe & Braet, 2005; Field et al., 2003; Tanofsky-Kraff et al., 2004) but not all (Claus, Braet, & Decaluwe, 2006;
Decaluwe & Braet, 2003; Decaluwe, Braet, & Fairburn, 2003; Glasofer et al., 2007) cross-sectional studies in children
support an association between dieting and binge eating. In one study, most children recalled the onset of LOC eating prior
to their first attempt at dieting (Tanofsky-Kraff et al., 2005), and another study found that only a minority endorsed having
eaten a forbidden food and/or restricting their food intake prior to an episode of LOC eating (Tanofsky-Kraff, Goossens et al.,
2007). Similarly inconsistent findings regarding the role of dieting in the etiology of BED are reported (e.g., Howard &
Porzelius, 1999; Spurrell, Wilfley, Tanofsky, & Brownell, 1997), and are in contrast to BN, in which dieting typically precedes
and helps maintain the disorder (e.g., Fairburn et al., 2003; Pederson Mussell et al., 1997). Taken together, data from the
child literature suggest the presence of other important variables besides, or in addition to, dieting behaviors and/or
cognitions in the onset of LOC eating in youth (e.g., Claus et al., 2006).
Despite the literature documenting associations between LOC eating and increased negative affect and dietary
restraint (Goossens et al., 2007; Tanofsky-Kraff et al., 2004), data regarding the validity of dietary restraint and dietary
restraint/negative affect subtypes in pediatric samples are limited. Subtyping youth with LOC eating for the presence of
dietary restraint and/or negative affect may have important research and clinical implications in terms of identifying
individuals at risk for comorbid psychopathology, highlighting relevant intervention foci, and predicting treatment
outcome. To our knowledge, only two studies have examined binge eating subtypes in pediatric samples, and both suggest
that the dietary restraint/negative affect subtyping scheme is a relatively robust phenomenon in youth as well. Indeed, the
dietary restraint/negative affect subtype has been associated with significantly greater eating-related and general
psychopathology across samples of adolescents with bulimia nervosa (Chen & Le Grange, 2007) and mixed symptoms of
disordered eating (e.g., binge eating, vomiting, fear of weight gain; Grilo, 2004). However, because both of these
studies were undertaken in adolescent samples, it remains unclear whether dietary restraint/negative affect subtypes can
be replicated in pre-adolescent samples as well. Moreover, it is unknown if the subtyping scheme is prevalent in youth
presenting with symptoms more consistent with BED (i.e., LOC eating in the absence of regular use of compensatory
behaviors).
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The aim of the current study was to determine whether the negative affect/dietary restraint subtyping scheme is
replicable and valid in children and adolescents with LOC eating problems. The current sample was enriched for
overweight, given that LOC eating is more prevalent among such individuals. We hypothesized that cluster analysis would
identify subtypes of youth characterized by mixed dietary restraint/negative affect, and pure dietary restraint.
Furthermore, based on previous findings in adults (Grilo, 2004; Grilo, Masheb, & Berman, 2001; Grilo, Masheb, & Wilson,
2001; Stice & Agras, 1999; Stice et al., 2001; Stice & Fairburn, 2003) and youth (Grilo, 2004; Chen & Le Grange, 2007), it was
expected that the dietary restraint/negative affect subtype would display greater eating-related psychopathology, LOC
eating severity, and parent-reported behavior problems as compared to the dietary restraint subtype.
Method
Participants
Participants were a convenience sample drawn from non-intervention protocols or weight loss treatment studies at five
research institutions (National Institute of Child Health and Human Development (NICHD), National Institutes of Health,
Maryland; University of Ghent, Belgium; Children’s Hospital Boston, Massachusetts; University of Pittsburgh Medical
Center, Pennsylvania; and Washington University School of Medicine, Missouri) to take part in a multi-site investigation of
factors surrounding binge eating in youth (Tanofsky-Kraff, Goossens et al., 2007). Given findings that LOC eating in children
is associated with elevated eating-related and general psychopathology irrespective of episode size (Goldschmidt et al.,
2008; Goossens et al., 2007; Tanofsky-Kraff et al., 2005), children from the larger multi-site study who reported any LOC
eating (i.e., at least one episode over the past 3 months) were included in the present study.
National Institute of Child Health and Human Development (NICHD), National Institutes of Health, Maryland
Studies at the NICHD involved overweight children and adolescents being assessed for weight loss intervention studies,
and overweight and non-overweight children and adolescents participating in non-intervention, metabolic studies.
Participants in the weight loss treatment studies were either aged 12–17, overweight, and with at least one obesity-related
comorbidity (e.g., hypertension, type 2 diabetes); or were 6–12 years old, overweight, and healthy other than having
evidence of insulin resistance. Treatment-seeking individuals were excluded if they had a major pulmonary, hepatic,
cardiac, or musculoskeletal disorder unrelated to obesity; a history of substance abuse or other psychiatric disorder that
would impair compliance with the study protocol; had used an anorexiant in the past 6 months; or had recently lost X5%
of their body weight.
Participants in the non-intervention studies (8–17 years) were healthy, other than some being overweight; medicationfree for at least 2 weeks prior to being studied; and without significant medical disease. Children were excluded if they had
a serious psychiatric disorder (e.g., psychosis) or an eating disorder other than BED, or if they were undergoing weight loss
treatment.
University of Ghent, Belgium
All participants (8–18 years) were overweight, and were either seeking inpatient weight loss treatment, or participating
in a non-intervention study of excess weight gain in childhood. Exclusion criteria at the University of Ghent site included
mental retardation, autism, or the presence of a developmental syndrome (e.g., Prader-Willi).
Children’s Hospital Boston, Massachusetts
Participants were overweight and at-risk-for-overweight children and adolescents (8–18 years) presenting for
behavioral weight loss treatment at the Optimal Weight for Life Clinic. Participants were excluded for the following
reasons: obesity-related disorders associated with mental retardation, psychotic disorders, or developmental disorders
associated with cognitive impairment.
University of Pittsburgh Medical Center, Pennsylvania
All participants (8–12 years) were involved in a non-intervention study examining mothers of overweight children.
Exclusion criteria for children included developmental delays precluding accurate completion of study assessments, use of
a medication that affects body weight, or recent initiation (less than 4 months) of stimulant or antidepressant medications.
Washington University School of Medicine, Missouri
Participants were overweight and at-risk-for-overweight adolescents (12–17 years) presenting for a study examining an
Internet-delivered weight loss intervention. Exclusion criteria included current or past diagnosis of a full-syndrome eating
disorder; medical conditions resulting in significant weight changes or precluding moderate physical activity; and use of
medication significantly affecting weight.
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Procedures
All treatment-seeking youth were assessed prior to entering weight loss treatment. After receiving a complete
description of the study, participants provided written assent and their parents provided written informed consent.
All protocols were approved by Institutional Review Boards at each respective site.
Measures
Demographics
Participants’ height and weight were measured and z-BMI (Kuczmarski et al., 2000) was calculated. Following CDC
standards (Ogden, Flegal, Carrol, & Johnson, 2002), children with a z-BMI at or above 1.64 (95th percentile) were identified
as overweight.
Eating Disorder Examination 12.0
At NICHD, weight-loss treatment-seeking adolescents aged 12–17 years, and non-treatment-seeking participants who
were 14 years or older completed the Eating Disorder Examination (EDE; Fairburn & Cooper, 1993). All other NICHD
participants, and children from the other four sites, regardless of participant age, were administered the EDE adapted for
children (ChEDE; Bryant-Waugh, Cooper, Taylor, & Lask, 1996). The EDE and ChEDE are semi-structured, interviewer-based
instruments for assessing behavioral and attitudinal correlates of eating disorders that are nearly identical in form and
content. Modifications found in the ChEDE include the use of simpler language to address comprehension concerns in
younger children, and the addition of a card-sort task to supplement items addressing over-valuation of shape and weight.
Both the adult and child versions of the interview have demonstrated very good reliability and validity (Bryant-Waugh et
al., 1996; Cooper, Cooper, & Fairburn, 1989; Decaluwe & Braet, 2004; Glasofer et al., 2007; Grilo, Masheb, Lozano-Blanco, &
Barry, 2004; Rizvi, Peterson, Crow, & Agras, 2000; Rosen, Vara, Wendt, & Leitenberg, 1990; Tanofsky-Kraff et al., 2004;
Watkins, Frampton, Lask, & Bryant-Waugh, 2005). The EDE yields four subscale scores (Restraint, Eating Concern, Weight
Concern, and Shape Concern) and a global score measuring the overall severity of eating disorder psychopathology, all of
which range in scores from 0 to 6. The EDE also contains diagnostic items that are used to arrive at a clinical diagnosis of an
eating disorder. Three types of eating episodes are distinguished according to the reported amount of food ingested, and
presence/absence of LOC: objective bulimic episodes (OBEs; episodes of LOC eating accompanied by consumption of an
unambiguously large amount of food); subjective bulimic episodes (SBEs; episodes of LOC eating not accompanied by
consumption of an unambiguously large amount of food, but considered excessive by respondents); and objective
overeating episodes (episodes consisting of an unambiguously large amount of food that are not accompanied by LOC).
As noted previously, only children with LOC eating (OBEs or SBEs) were included in the present study.
Children’s Depression Inventory
The Children’s Depression Inventory (CDI; Kovacs, 1985) was used to assess depressive symptoms. CDI scores range from
0 to 54, and a clinical cutoff score of 19 is used to indicate probable depression (Kovacs, 1992). The CDI is well-established
in terms of its test–retest reliability, internal consistency, and construct validity (Sitarenios & Kovacs, 1999). It has been
found to correlate modestly with clinician reports of depression (Kazdin, 1989), and to distinguish between children with
depression and those with other forms of psychopathology (Carlson & Cantwell, 1980).
Child Behavior Checklist
The Child Behavior Checklist (CBCL; Achenbach, 1991) is a parent-reported measure of child competency and
functioning in a range of behavioral domains. The CBCL generates eight clinical subscales, internalizing and externalizing
scales, a total problems scale, and a competence scale, with scores ranging from 0 to 100. The CBCL has demonstrated good
reliability and validity (Achenbach, 1991; Achenbach & Elderbrock, 1991). For the purposes of the present study, only the
internalizing, externalizing, and total problems scales were examined.
Statistical analysis
All analyses were conducted using SPSS for Windows, version 14.0 (SPSS, 2005). The sample size (n ¼ 159) provided
greater than 80% power to detect a medium effect size (Lenth, 2006). Participants were subject to a k-means cluster
analysis, based on EDE Restraint subscale and CDI total scores. This procedure attempts to identify relatively homogeneous
groups of cases based on selected characteristics, using a pre-determined number of clusters. A two-cluster solution was
specified given findings from the adult literature. Raw Restraint and CDI scores were selected based on the
recommendation of Stoddard (1979), because standardizing scores can eliminate important variability between clusters,
and can reduce the natural weighting established by differences in measurement scales. Initial cluster centers (each case in
a given cluster’s average value on all clustering variables) were chosen by selecting the two cases that differed most on the
chosen variables. Cluster centers were updated iteratively based on each case’s Euclidean distance from its center. Once all
cases were assigned to a cluster, a new center was calculated before the next cluster assignment, and the procedure
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repeated for up to 10 iterations. Participants with missing data on either of the clustering measures (n ¼ 13) were not
assigned to a cluster. Independent samples t-tests and Pearson Chi-square tests were used to explore cluster differences in
age, sex, treatment-seeking status, site, and z-BMI. CDI and Restraint scores were compared as a manipulation check, to
determine replication of the dietary restraint and dietary restraint/negative affect subtypes in the current sample; t-test
results are presented for descriptive purposes. Separate MANCOVAs were used to compare clusters on EDE subscales, and
on CBCL subscales. Given their non-normality, past month OBE and SBE frequencies were subject to log transformations,
and ANCOVA was used to compare the clusters on these variables. Because of the very low reported frequency of
compensatory behaviors (i.e., self-induced vomiting, laxative use, diuretic use, and driven exercise), the sample was divided
into those who did and did not report any compensatory behaviors during the past month. Clusters were then compared on
this variable using Chi-square analyses.
In order to validate the clusters, as suggested by Rapkin and Luke (1993), the dataset was divided into two random
subsamples and the cluster analysis was re-run in each of these subsamples. T-tests were used to compare clusters within
each of these samples on the clustering variables, and planned contrasts following an ANOVA with a nested design (cluster
nested within sample) were used to compare the clusters across subsamples. The cluster analysis was also re-run on
treatment-seeking and non-treatment-seeking individuals, as well as individuals reporting binge eating (i.e., OBEs); t-tests
were used to compare clusters within each of these samples on the clustering variables. Separate MANOVAs and
MANCOVAs (when appropriate) were performed on the remaining EDE subscales, and on CBCL subscales to compare
clusters within each of these subsamples.
Results
Sample characteristics
The original sample consisted of 445 children and adolescents (59.1% females), aged 8–18 years (M age ¼ 13.272.7),
participating in the multi-site study (M z-BMI ¼ 1.870.9; Tanofsky-Kraff, Goossens et al., 2007). From this sample, 172
children and adolescents (62.8% females; M age ¼ 12.872.9 years) were selected for the current study based on reporting
LOC eating, with or without consumption of an unambiguously large amount of food. These 172 participants were 60.5%
Caucasian; 28.5% African-American; 8.1% Hispanic; 1.2% Asian; and 1.7% identified themselves as ‘‘other.’’ The majority
(80.2%) of participants were overweight, with an age- and sex-adjusted body mass index (z-BMI; Ogden et al., 2002) greater
than the 95th percentile (M z-BMI ¼ 2.070.7), and 50.6% were seeking weight-loss treatment. See Table 1 for sample
characteristics.
Full sample cluster analysis
In the full sample, cluster analysis produced two subtypes, one characterized by moderate dietary restraint
(DR; n ¼ 114; 71.7%) and the second by a mixed presentation combining moderate dietary restraint and high negative
affect (DR/NA; n ¼ 45; 28.3%). The mean CDI score of 19.875.0 in the DR/NA cluster corresponds to probable depression; in
contrast, the mean CDI score of 6.773.7 in the DR cluster indicates low probability of depression (t ¼ 15.9; po0.001). The
DR/NA and DR subtypes reported mean Restraint scores of 1.471.0 and 1.070.9 (t ¼ 2.3; p ¼ 0.02), respectively, indicating
that both groups attempted to exercise restraint approximately on 1–5 days in the preceding 4 weeks.
Demographics
The DR/NA cluster was significantly older than the DR cluster; disproportionately more DR/NA cases were seeking
treatment; and the Missouri and Belgium sites had disproportionately more DR/NA cases, and the NIH site
disproportionately more DR cases, than expected given the ratio of DR/NA to DR cases in the full sample (all pso0.01).
The clusters did not significantly differ in race/ethnicity, z-BMI, or sex (all psX0.24). Age, site, and treatment-seeking status
were considered as covariates in all subsequent analyses, however, neither age nor site significantly contributed to the
ANCOVA and MANCOVA models, thus, only treatment-seeking status was retained as a covariate in subsequent analyses.
Sex was also included as a covariate given its established association with all of the dependent variables (Crick & ZahnWaxler, 2003; Presnell, Bearman, & Stice, 2004; Twenge & Nolen-Hoeksema, 2002; Vander Wal & Thelen, 2000). See Table 1
for cluster characteristics.
Subtype comparisons on psychopathology
The clusters significantly differed on shape and weight concerns, and on global severity of disordered eating symptoms
(all pso0.05), with the DR/NA cluster scoring higher than the DR cluster on these measures; differences on eating concerns
approached significance (p ¼ 0.06). The DR/NA cluster reported a greater frequency of OBEs over the past month relative to
the DR cluster (p ¼ 0.05), whereas there were no differences in SBE frequency. The DR/NA subtype also exhibited
significantly greater CBCL internalizing, externalizing, and total scores (all pso0.001) than the DR cluster. See Table 1 for
subtype comparisons on EDE and CBCL scores.
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Table 1
Full sample characteristics and comparisons between dietary restraint and dietary restraint/negative affect subtypes on demographic and psychosocial
variables (M7S.D., unless otherwise indicated)
Variable
Demographic variables
Female, % (n)
Age, years
z-BMI
Race, % (n)
White
Black
Hispanic
Asian
Other
Treatment seeking, % (n)
Full sample (n ¼ 172)a
DR/NA (n ¼ 45)
DR (n ¼ 114)
Statistic
62.8 (108)
12.872.9
2.070.7
55.6 (25)
13.972.5
2.170.6
63.2 (72)
12.572.9
1.970.8
w2 ¼ 0.8
t ¼ 3.0
t ¼ 1.3
w2 ¼ 2.5
60.5
28.5
8.1
1.2
1.7
50.6
60.0
33.3
6.7
0.0
0.0
66.7
56.1
29.8
9.6
1.8
2.6
37.7
(104)
(49)
(14)
(2)
(3)
(87)
(27)
(15)
(3)
(0)
(0)
(30)
(64)
(34)
(11)
(2)
(3)
(43)
w2 ¼ 10.9
Eating related psychopathology
EDE Restraint
EDE Eating Concern
EDE Shape Concern
EDE Weight Concern
EDE Global
SBE frequencyb
OBE frequencyb
Compensatory behaviors, % (n) reportingc
1.170.9
0.870.8
2.271.4
2.371.2
1.670.9
1.272.8
2.374.9
6.4 (11)
1.471.0
1.171.0
2.871.4
2.871.1
2.070.9
1.172.6
4.277.6
4.4 (2)
1.070.9
0.770.7
2.071.4
2.171.2
1.470.8
1.473.0
1.673.5
7.0 (8)
t ¼ 2.3
F ¼ 3.6
F ¼ 6.6
F ¼ 5.7
F ¼ 8.5
F ¼ 0.0
F ¼ 4.0
w2 ¼ 0.5
General psychopathology
CDI Total
CBCL Internalizing
CBCL Externalizing
CBCL Total
10.477.2
55.7713.3
52.1713.0
55.6712.9
19.875.0
62.8711.3
58.8712.0
63.1711.2
6.773.7
51.9712.4
49.0712.4
51.8711.8
t ¼ 15.9
F ¼ 19.9
F ¼ 14.4
F ¼ 21.9
Note: DR/NA, dietary restraint/negative affect subtype; DR, dietary restraint subtype; z-BMI, body mass index z-score accounting for age and sex (Ogden et
al., 2002); EDE, Eating Disorder Examination; OBE, objective bulimic episode; SBE, subjective bulimic episode; CDI, Children’s Depression Inventory; CBCL,
Child Behavior Checklist.
a
Thirteen participants from the full sample were excluded from the cluster analysis because of missing data.
b
Reported eating episode frequencies are for the month prior to assessment only.
c
Compensatory behaviors include self-induced vomiting, laxative use, diuretic use, and driven exercise. The rates reported pertain to the number of
participants endorsing use of any of these behaviors in the month prior to assessment.
po0.05.
po0.01.
po0.001.
Replication in random subsamples
When the cluster analysis was re-run in two random subsamples (Sample 1, n ¼ 80; Sample 2, n ¼ 79), results were
identical to those obtained in the full sample cluster analysis. One cluster from Samples 1 (n ¼ 21; 26.3%) and 2 (n ¼ 24;
30.4%) exhibited a pattern of high negative affect and moderate dietary restraint, whereas the other cluster from Samples 1
(n ¼ 59; 73.8%) and 2 (n ¼ 55; 69.6%) exhibited low negative affect and moderate dietary restraint (see Table 2). These
clusters will henceforth be referred to as DR/NA-1 and DR/NA-2, and DR-1 and DR-2, respectively, referring to their levels of
negative affect and dietary restraint, and the subsamples from which they were derived. The DR/NA and DR clusters within
each sample significantly differed from one another in CDI scores (all pso0.001), but not in Restraint scores (psX0.11).
DR/NA-1 significantly differed from DR-2 in CDI scores (contrast estimate ¼ 13.42; po0.001), but did not significantly
differ from DR/NA-2 in CDI scores (contrast estimate ¼ 0.11; p ¼ 0.93). DR/NA-1 did not significantly differ in Restraint
from DR/NA-2 (contrast estimate ¼ 0.12; p ¼ 0.67) or DR-2 (contrast estimate ¼ 0.24; p ¼ 0.32).
There were no differences between DR-1 and DR/NA-1 subtypes on demographic variables. However, DR/NA-2
was significantly older (t ¼ 2.6; p ¼ 0.01) and heavier (t ¼ 2.2; p ¼ 0.03) than DR-2, thus, subsequent MANCOVAs
controlled for these variables. Comparisons between DR and DR/NA subtypes in each of these random subsamples are
described in Table 2.
Replication in treatment-seeking and non-treatment-seeking youth
Treatment-seeking youth were significantly heavier (t ¼ 6.9; po0.001) and comprised of disproportionately more
Hispanic and fewer Caucasian youth (w2 ¼ 19.6; p ¼ 0.001) than non-treatment youth. When controlling for z-BMI and
race/ethnicity, treatment-seeking youth reported significantly higher scores on EDE Eating Concern, Weight Concern, and
Global scores (psp0.03); CDI total (po0.001); and CBCL internalizing, externalizing, and total scores (psp0.001).
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Table 2
Comparisons between dietary restraint and dietary restraint/negative affect subtypes on psychosocial variables within two random samples (M7S.D.)
Measure
EDE Restraint
EDE Eating Concern
EDE Shape Concern
EDE Weight Concern
EDE Global
CDI Total
CBCL Internalizing
CBCL Externalizing
CBCL Total
Sample 1 (n ¼ 80)
Sample 2 (n ¼ 79)
DR/NA-1 (n ¼ 21)
DR-1 (n ¼ 59)
M7S.D.
M7S.D.
1.371.1
1.070.9
2.571.2
2.571.0
1.870.8
19.975.3
65.7713.1
60.8711.5
65.7712.4
0.970.8
0.870.8
2.271.4
2.371.1
1.570.8
6.973.6
52.2714.1
50.3714.5
53.5712.5
DR/NA-2 (n ¼ 24)
DR-2 (n ¼ 55)
Statistic
M7S.D.
M7S.D.
Statistic
t ¼ 1.6
F ¼ 1.4
F ¼ 0.7
F ¼ 0.5
F ¼ 2.0
t ¼ 10.4
F ¼ 15.8
F ¼ 9.2
F ¼ 14.2
1.470.9
1.271.1
3.171.6
3.071.1
2.270.9
19.874.9
60.379.0
57.1712.4
61.0710.0
1.171.0
0.770.7
1.871.4
1.971.3
1.370.9
6.473.8
51.6710.4
47.579.6
50.0710.9
t ¼ 1.5
F ¼ 2.0
F ¼ 6.6
F ¼ 7.6
F ¼ 6.5
t ¼ 13.1
F ¼ 6.5
F ¼ 8.8
F ¼ 9.7
Note: DR/NA-1, dietary restraint/negative affect subtype in Sample 1; DR-1, dietary restraint subtype in Sample 1; DR/NA-2, dietary restraint/negative
affect subtype in Sample 2; DR-2, dietary restraint subtype in Sample 2; EDE, Eating Disorder Examination; CDI, Children’s Depression Inventory; CBCL,
Child Behavior Checklist.
po0.05.
po0.01.
po0.001.
Table 3
Comparisons between dietary restraint and dietary restraint/negative affect subtypes on psychosocial variables within treatment-seeking and nontreatment-seeking youth (M7S.D.)
Measure
EDE Restraint
EDE Eating Concern
EDE Shape Concern
EDE Weight Concern
EDE Global
CDI Total
CBCL Internalizing
CBCL Externalizing
CBCL Total
Treatment-seeking youth (n ¼ 74)
Non-treatment-seeking youth (n ¼ 85)
DR/NA-TX (n ¼ 29)
DR-TX (n ¼ 45)
DR/NA-NOTX (n ¼ 27)
DR-NOTX (n ¼ 58)
M7S.D.
M7S.D.
Statistic
M7S.D.
M7S.D.
Statistic
1.370.9
1.271.0
3.171.3
3.071.0
2.170.7
21.374.4
65.5711.1
61.7711.4
66.079.5
1.270.9
1.170.9
2.571.3
2.571.1
1.870.8
7.473.4
55.579.9
52.079.8
55.279.4
t ¼ 0.3
F ¼ 0.1
F ¼ 1.4
F ¼ 3.8
F ¼ 1.6
t ¼ 15.2
F ¼ 11.2
F ¼ 12.9
F ¼ 14.4
1.371.1
0.670.8
1.871.5
1.871.2
1.470.9
14.974.6
55.9710.9
54.2712.8
56.9711.8
0.870.9
0.670.7
1.871.4
1.971.2
1.270.9
5.173.1
49.0713.6
45.5712.9
48.7712.8
t ¼ 2.3
F ¼ 0.2
F ¼ 0.0
F ¼ 0.1
F ¼ 0.3
t ¼ 11.4
F ¼ 5.0
F ¼ 8.2
F ¼ 7.7
Note: DR/NA-TX, dietary restraint/negative affect subtype in treatment-seeking youth; DR-TX, dietary restraint subtype in treatment-seeking youth; DR/
NA-NOTX, dietary restraint/negative affect subtype in non-treatment-seeking youth; DR-NOTX, dietary restraint subtype in non-treatment-seeking
youth; EDE, Eating Disorder Examination; CDI, Children’s Depression Inventory; CBCL, Child Behavior Checklist.
po0.05.
po0.01.
po0.001.
Within the treatment-seeking sample, the first cluster (n ¼ 29; 39.2%) exhibited a pattern of high negative affect and
moderate dietary restraint, whereas the second cluster within treatment-seekers (n ¼ 45; 60.8%) endorsed low negative
affect and moderate dietary restraint (see Table 3). These clusters will henceforth be referred to as DR/NA-TX and DR-TX,
respectively, referring to their levels of negative affect and dietary restraint, and the treatment-seeking subsample from
which they were derived. The DR/NA-TX cluster demonstrated significantly greater CDI scores than the DR-TX cluster
(po0.001), whereas the groups did not differ in Restraint (p ¼ 0.76). The DR/NA-TX cluster was significantly older (t ¼ 3.3;
p ¼ 0.002) than the DR-TX cluster, thus, subsequent analyses controlled for age. MANCOVA comparisons on other
psychosocial variables are reported in Table 3.
Within non-treatment-seeking youth, the first cluster (n ¼ 27; 31.8%) reported moderate negative affect and moderate
dietary restraint, whereas the second cluster (n ¼ 58; 68.2%) endorsed low negative affect and low dietary restraint (see
Table 3). These clusters will henceforth be referred to as DR/NA-NOTX and DR-NOTX, respectively, referring to their levels
of negative affect and dietary restraint, and the non-treatment subsample from which they were derived. The two clusters
significantly differed in CDI scores (po0.001) and in Restraint scores (p ¼ 0.03), with the DR/NA-NOTX cluster scoring
higher in these domains. There were no differences between DR-NOTX and DR/NA-NOTX subtypes on demographic
variables. MANOVA comparisons on other psychosocial variables are reported in Table 3.
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Table 4
Comparisons between dietary restraint and dietary restraint/negative affect subtypes on psychosocial variables within youth reporting binge eating
(M7S.D.)
Measure
EDE Restraint
EDE Eating Concern
EDE Shape Concern
EDE Weight Concern
EDE Global
CDI Total
CBCL Internalizing
CBCL Externalizing
CBCL Total
Youth reporting binge eating (n ¼ 66)
DR/NA-OBE (n ¼ 30)
DR-OBE (n ¼ 66)
M7S.D.
M7S.D.
Statistic
1.371.0
1.271.0
3.071.4
2.971.0
2.170.8
21.175.0
65.7711.6
61.0712.1
65.4710.4
1.07.09
0.870.8
2.171.5
2.171.2
1.570.9
7.673.8
53.0712.0
51.1712.6
54.4711.0
t ¼ 1.6
F ¼ 1.2
F ¼ 2.2
F ¼ 5.3
F ¼ 4.0
t ¼ 14.6
F ¼ 14.3
F ¼ 10.7
F ¼ 11.9
Note: DR/NA-OBE, dietary restraint/negative affect subtype in youth reporting objective bulimic episodes; DR-OBE, dietary restraint subtype in youth
reporting objective bulimic episodes; EDE, Eating Disorder Examination; CDI, Children’s Depression Inventory; CBCL, Child Behavior Checklist.
po0.05.
po0.01.
po0.001.
Replication in youth reporting binge eating
Within youth reporting OBEs (n ¼ 96), the first cluster (n ¼ 30; 31.2%) reported high negative affect and moderate
dietary restraint, whereas the second cluster (n ¼ 66; 68.8%) reported low negative affect and moderate dietary restraint.
These clusters will henceforth be referred to as DR/NA-OBE and DR-OBE, respectively, referring to their levels of negative
affect and dietary restraint, and the ‘‘pure’’ binge eating sample from which they were derived. The DR/NA-OBE cluster
demonstrated significantly greater CDI scores than the DR-OBE cluster (po0.001), whereas the groups did not differ in
Restraint (p ¼ 0.11). The DR/NA-OBE cluster was significantly older (t ¼ 3.9; po0.001) and heavier (t ¼ 2.2; p ¼ 0.03) than
the DR-OBE cluster, thus, subsequent analyses in youth reporting binge eating controlled for z-BMI and age. MANCOVA
results are reported in Table 4.
Discussion
The current study examined the validity of subtyping youth with LOC eating problems along dietary restraint and negative
affect dimensions. Cluster analysis yielded two subtypes: pure dietary restraint (DR), and mixed dietary restraint and high
negative affect (DR/NA). These subtypes were replicated in two randomly selected subsamples of the dataset, in treatmentseeking youth, and in youth reporting ‘‘pure’’ binge eating. In the overall sample, the DR/NA subtype exhibited greater eatingrelated psychopathology and parent-reported behavior problems as compared to the DR subtype; similar results were
generally observed across subsamples. No differences between subtypes were found with regard to body weight.
The cluster arrangements that emerged in the full sample were relatively robust, as indicated by their replication in
random samplings of the data, in treatment-seeking individuals, and in youth reporting binge eating. Further, in both the
full sample and in the subsample replications, the proportion of individuals in each cluster (i.e., approximately 70% in the
DR cluster, versus 30% in the DR/NA cluster) was comparable to distributions found in the adult literature (Grilo, Masheb, &
Berman, 2001; Grilo, Masheb, & Wilson, 2001; Stice & Agras, 1999; Stice et al., 2001; Stice & Fairburn, 2003). Therefore, our
findings indicate that, similar to adults with BED and BN (Grilo, Masheb, & Berman, 2001; Grilo, Masheb, & Wilson, 2001;
Stice & Agras, 1999; Stice et al., 2001; Stice & Fairburn, 2003), youth may be subtyped based upon dietary restraint and
negative affect. While both clusters endorsed relatively low levels of restraint, both scored above normative Restraint
subscale means for overweight youth (Decaluwe & Braet, 2004), indicating that modest dietary restraint may be a core
feature of LOC eating in youth. Moreover, given the findings that, similar to the adult literature (Grilo, Masheb, & Berman,
2001; Grilo, Masheb, & Wilson, 2001; Stice & Agras, 1999; Stice et al., 2001; Stice & Fairburn, 2003), the DR/NA subtype in
the full sample exhibited more frequent binge eating, and greater disordered eating psychopathology and parent-reported
behavior problems than the DR subtype, our data suggest that the presence of negative affect may signal a more severe
variant of LOC eating in children and adolescents and that this additional impairment may be related, at least in part, to
negative affect. Indeed, the higher shape and weight concerns observed in the DR/NA cluster relative to the DR cluster may
imply greater risk for a full-syndrome eating disorder among this subgroup, given that such concerns have been identified
as a risk factor for eating disorders (Jacobi, Hayward, de Zwaan, Kraemer, & Agras, 2004). It is notable that the difficulties
experienced by youth with concomitant depressive symptoms and LOC eating were not limited to the eating disorder
arena, but also were evident in their tendencies to internalize and externalize emotions based upon parent-reports.
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785
When analyses were repeated based upon treatment-seeking status, a somewhat different pattern was observed in nontreatment youth compared to treatment-seeking children and the sample as a whole: for the non-treatment sample, one
cluster was characterized by moderate dietary restraint and moderate negative affect, the other by low dietary restraint
and low negative affect. Both clusters in the non-treatment sample evidenced relatively low CDI scores; however, the mean
CDI score for the full non-treatment sample was also quite low, and significantly lower than the mean CDI score for the
treatment-seeking sample (as were scores on most other measures of psychopathology). This is consistent with our finding
that, in the full study sample, the DR/NA subtype was significantly more likely to be seeking treatment than the DR
subtype, suggesting that depressive symptoms may be in part responsible for motivating families to seek weight control
treatment for children. For those children exhibiting LOC eating and both low depressive symptoms and low levels of
dietary restraint (i.e., the non-treatment-seeking DR subtype), there may be a separate pathway to LOC eating that involves
neither negative affect nor restraint (e.g., impulsivity; Nederkoorn, Braet, Van Eijs, Tanghe, & Jansen, 2006); further
research is needed to delineate risk factors for LOC eating in this group. Clinically, children who have not yet reached the
point where they seek professional treatment may be a more optimal group with whom to intervene for preventive efforts,
given that their LOC eating status may promote weight gain or development of a full-syndrome eating disorder (Kotler,
Cohen, Davies, Pine, & Walsh, 2001; Tanofsky-Kraff et al., 2006). Their modest levels of depressive symptomatology are
unlikely to interfere with treatment, in contrast to the poorer treatment outcome observed in some studies of binge eating
adults with high negative affect (Stice & Agras, 1999; Stice et al., 2001).
Our findings may have important clinical implications. Practitioners are advised to assess for depressive symptoms in
children and adolescents presenting with binge or LOC eating problems, since the presence of negative affect concurrent
with eating disorder behaviors appears to indicate a more severely impaired subset of these youth. It may be necessary for
clinical attention to focus on other presenting symptoms as well. However, it is unclear whether youth with high negative
affect and moderate dietary restraint can be expected to respond as well as those with pure dietary restraint to
psychological treatments designed to treat LOC eating, given that some adult studies have found poorer binge eating
treatment outcome in the negative affect/dietary restraint subtype as noted above (Stice & Agras, 1999; Stice et al., 2001).
Future studies examining treatment outcome in the different subtypes of youth with binge or LOC eating problems are
needed to determine whether the DR/NA subtype is in need of more intensive or differential care.
Several limitations of this investigation should be noted. Our study design was cross-sectional, precluding conclusions
about causality of depressive and eating disorder symptoms. Prospective studies indicate that negative affect may predict
binge eating onset in adolescents (Stice & Agras, 1998; Stice et al., 1998) and, simultaneously, binge eating predicts further
increases in depressive symptoms (Stice & Bearman, 2001; Stice, Burton, & Shaw, 2004; Stice, Hayward, Cameron, Killen, &
Taylor, 2000). However, it is unclear how other forms of psychopathology (e.g., shape and weight concerns, internalizing
and externalizing symptoms) may interact with one another in the onset and/or outcome of these problems. Further, the
use of a sample in which few participants met criteria for BED precludes generalization to youth with full-syndrome eating
disorders. Finally, behavior problems were reported by parents only; given the generally poor agreement between parents
and children on measures of behavior problems (e.g., Jensen et al., 1999), future studies should include child-reports of
their own behavioral problems as well. Strengths of this study include the use of a large and diverse sample in terms of
treatment-seeking status, location, and cultural background. Other study strengths include the use of interview
methodology for assessing eating disordered behavior and attitudes, and standardized measurement, rather than selfreports, of height and weight to calculate BMI.
In summary, the present study extends the adult literature by indicating that dietary restraint and dietary restraint/high
negative affect subtypes can be identified in youth with LOC eating problems. Further examination of these subtypes in
youth is warranted in order to understand their associations with functioning in other domains, with other forms of
psychopathology, and with treatment response. Prospective studies are required to determine whether youth belonging to
the dietary restraint/negative affect subtype are at greater risk for developing a full-syndrome eating disorder or other
psychiatric disorders and thus might benefit from preventive interventions.
Acknowledgments
Funding sources for this study include NIH Grants T32 HL007456 (Ms. Goldschmidt), K24 MH070446 (Dr. Wilfley), F31
MH071019 (Dr. Eddy), and the Pittsburgh Mind-Body Center (NIH Grants HL076852/076858; Drs. Ringham and Marcus). Dr.
J. Yanovski is a Commissioned Officer in the US Public Health Service. This research was supported in part by the Intramural
Research Program of the NIH, Grant Z01 HD00641 (to Dr. J. Yanovski) from the National Institute of Child Health and
Human Development, National Institutes of Health.
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